ElectrifAi Software Engineer Interview Questions and Answers

Employee model CRUD APIS USING SRPING BOOT & MYSQL

Q1. TELL ME ABOUT YOUR SELF
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Q2. SPRING BOOT VS SPRING
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Spring Boot is a framework that simplifies Spring development by providing pre-configured settings and dependencies.
• Spring Boot is built on top of the Spring framework.

• Spring Boot provides a standalone executable that can run the application.

• Spring Boot provides auto-configuration, which reduces the need for manual configuration.

• Spring Boot provides a wide range of starter dependencies that can be easily added to the p...read more
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Q3. JPA VS HIBERNATE WHAT IS ADVANTAGE USING JPA
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JPA is a specification while Hibernate is an implementation of JPA. JPA provides a standard API for ORM frameworks.
• JPA is a standard API for ORM frameworks

• JPA provides a vendor-neutral interface

• JPA allows for easy switching between ORM frameworks

• Hibernate is an implementation of JPA

• Hibernate provides additional features beyond JPA
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Q4. WHTA IS MYSQL GROUP BY & DISTINCT
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MySQL GROUP BY is used to group rows with same values. DISTINCT is used to remove duplicate values from a column.
• GROUP BY is used with aggregate functions like COUNT, SUM, AVG, etc.

• DISTINCT is used to retrieve unique values from a column.

• GROUP BY and DISTINCT can be used together to group and retrieve unique values.

• Example: SELECT COUNT(*) FROM table_name GROUP BY column_name;

• Example: SELECT DISTINCT column_name FROM t
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Q5. WHAT ARE SCOPES ARE AVAILABLE IN SPRING
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Spring has four scopes: Singleton, Prototype, Request, and Session.
• Singleton scope creates a single instance of a bean.

• Prototype scope creates a new instance of a bean every time it is requested.

• Request scope creates a new instance of a bean for each HTTP request.

• Session scope creates a new instance of a bean for each HTTP session.
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Q1. Basic Technical Interview
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Q2. Basics on Framework used
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Q3. Infrastructure related
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Q4. Process and security
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Q1. Salary expectations and negotiation
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Strong appitude knowledge is required.

Q1. String , arrays, oops
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Q1. Strecture of sql statement
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SQL statements are used to interact with databases by performing operations like querying, updating, and deleting data.
• SQL statements are made up of keywords like SELECT, INSERT, UPDATE, DELETE, etc.

• They are structured in a specific order, with clauses like WHERE, ORDER BY, GROUP BY, etc.

• Tables are referenced using their names, and conditions are specified to filter data.

• Joins can be used to combine data from multiple
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Quantitative Aptitude

Stakeholders vs Shareholders

Analysis of financial time series

Q1. Basic mathematics question, basic English and SQL questions
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Q1. Resume based questions
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Q2. Different types of commands
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Different types of commands include data manipulation, data definition, data control, and transaction control commands.
• Data manipulation commands: SELECT, INSERT, UPDATE, DELETE

• Data definition commands: CREATE, ALTER, DROP

• Data control commands: GRANT, REVOKE

• Transaction control commands: COMMIT, ROLLBACK, SAVEPOINT
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Q3. Difference between inner join and outer join
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Inner join returns only the matching rows between two tables, while outer join returns all rows from both tables.
• Inner join only includes rows that have matching values in both tables

• Outer join includes all rows from both tables, filling in missing values with NULL if there is no match

• Examples: Inner join - SELECT * FROM table1 INNER JOIN table2 ON table1.id = table2.id; Outer join - SELECT * FROM table1 LEFT OUTER JOI
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Q4. Write SQL query to get second highest salary
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SQL query to retrieve the second highest salary from a table
• Use the ORDER BY clause to sort salaries in descending order

• Use the LIMIT clause to retrieve the second row
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Q5. What's the difference between numpy and pandas
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Numpy is a library for numerical operations in Python, while Pandas is used for data manipulation and analysis.
• Numpy is used for numerical operations like linear algebra, Fourier transform, etc.

• Pandas is used for data manipulation tasks like data cleaning, merging, reshaping, etc.

• Numpy works with arrays, while Pandas works with dataframes.

• Numpy is more efficient for numerical computations, while Pandas is more user-fri...read more
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